In some MMS applications, the primary intention is to capture pictures of building facades and other fixed objects, like trees, street signs and street lamps that are later used in “real-world” 2D and/or 3D images of streets used in e.g. car navigation systems. Then, these images are shown to drivers of a car provided with such a navigation system such that the driver sees 2D and/or 3D images on a screen of the navigation system corresponding with the real world view when looking through the windows of the car. Such pictures may also be used in other applications than car navigation systems, for instance, in games that can be played on computers either as a stand alone system or as cooperating in a networked environment. Such an environment may be the Internet. The solution of the present invention as presented below is not restricted to a specific application.
The pictures are collected and stored and involve an enormous data size, as many pictures are taken to cover a substantial part of a road network. The picture data thus comprises many frames of imagery, possibly from multiple cameras. In order to reduce the picture data to manageable size, compression techniques may be applied. Generally image quality is inversely related to the amount of compression. This may be disadvantageous when items such as traffic signs need to remain recognizable/legible despite possible compression techniques being applied to the picture data
According to the prior art, the technique of identifying different regions of interest in each picture and using a first compression factor (relatively high) in a first region of interest and using a second compression factor (relatively low) in a second region of interest is known. This ensures that relatively high data size reduction is achieved, while not discarding valuable information, such as traffic signs. This technique is referred to as differential compression of raster images (i.e. camera data) and is a major component of modern document scanning and compression systems.
Most of these prior art solutions (i.e., Luratech's LuraDocument) use text recognition as a means of identifying regions of interest. The underlying assumption of such systems is that non-textual areas can be compressed at a higher rate (i.e., with more loss). Such algorithms are computationally expensive and complex, and if applied to the MMS data would need significant investment in computer power. Also, text recognition algorithms may require assumptions about font, spacing, rotation of the text to recognize. Most important, such techniques are limited to identifying regions of interest comprising text.
Document PCT/NL2006/050269, which was filed Oct. 30, 2006 and not published at the time of filing of this patent application, describes a system for supporting image recognition by finding regions in the image using a scanner, to identify certain objects. PCT/NL2006/050269 only refers to finding regions, but does not address the problem of managing the amount of camera data.
Document PCT/NL2007/050541, which was filed Nov. 7, 2007 and not published at the time of filing of this patent application, describes how scanner data may be used to identify certain objects, for instance to remove privacy sensitive data from the camera data. Again, this document does not address the problem of managing the amount of camera data.